کاربرد مدل‌های فراکتالی دو و سه‌فازی در برآورد هدایت هیدرولیکی اشباع خاک

نوع مقاله : مقالات پژوهشی

نویسندگان

دانشگاه ارومیه

چکیده

هدایت هیدرولیکی خاک یکی از مهمترین خصوصیات هیدرولیکی در حرکت آب و املاح در محیط متخلخل به شمار می‌رود. در سال‌های اخیر‏، مدل‌های متعددی به صورت توابع انتقالی، مدل‌های فراکتالی‏، مدل‌های تجربی و تکنیک مقیاس‌سازی به منظور برآورد هدایت هیدرولیکی اشباع بکار گرفته شده است. ‏هدف اصلی تحقیق حاضر‏، ارزیابی مدل‌های فراکتالی مختلف در برآورد پارامتر هدایت هیدرولیکی اشباع خاک می‌باشد. به این منظور از مدل راولزو داده‌های اسخاپ و همکاران مشتمل بر شصت نمونه خاک استفاده شده است. در این مجموعه، بافت خاک به روش هیدرومتری‏، وزن مخصوص ظاهری به روش نمونه دست نخورده، هدایت هیدرولیکی اشباع با روش آزمایشگاهی بار ثابت‏، منحنی دانه‌بندی خاک به روش الک خیس و منحنی نگهداشت آب خاک به روش دستگاه صفحات فشاری برای تمام نمونه‌های خاک اندازه‌گیری شده است. نتایج تحقیق بیانگر برتری‏ مدل سه‌فاز یهانگ و زانگبا بالاترین میزان همبستگی‏، کمترین ریشه مجذور مربعات خطا (cm/h 41/0RMSE=) و آکائیک (cm/h 63/-0AIC=) در بین مدل‌های فراکتالی مورد مطالعه، در برآورد هدایت هیدرولیکی اشباع می‌باشد. با توجه به نتایج آنالیز حساسیت، مدل ترکیبی راولز- هانگ کمترین حساسیت را نسبت به تغییرات تخلخل و مکش ورود هوا و بیشترین حساسیت را نسبت به تغییرات بعد فراکتال دارد. بررسی شاخص‌های خطا‏، بیانگر بالا بودن دقت برآورد هدایت هیدرولیکی اشباع در ترکیب مدل‌های سه‌فازی (PSF) مبتنی بر داده‌های بافت خاک با مدل راولز می‌باشد. نتایج نشان می‌دهد با وجود اینکه تمام نمونه‌های مورد بررسی دارای کمتر از 8 درصد رس در ترکیب خود می‌باشند، اما میزان رس خاک در برآورد بعد فراکتالی نقش تعیین‌کننده‌ و اساسی برخوردار است‏.

کلیدواژه‌ها


عنوان مقاله [English]

Two and Three-Phases Fractal Models Application in Soil Saturated Hydraulic Conductivity Estimation

نویسندگان [English]

  • ELNAZ Rezaei abajelu
  • KAMRAN Zeinalzadeh
Urmia University
چکیده [English]

Introduction: Soil Hydraulic conductivity is considered as one of the most important hydraulic properties in water and solutionmovement in porous media. In recent years, variousmodels as pedo-transfer functions, fractal models and scaling technique are used to estimate the soil saturated hydraulic conductivity (Ks). Fractal models with two subset of two (solid and pore) and three phases (solid, pore and soil fractal) (PSF) are used to estimate the fractal dimension of soil particles. The PSF represents a generalization of the solid and pore mass fractal models. The PSF characterizes both the solid and pore phases of the porous material. It also exhibits self-similarity to some degree, in the sense that where local structure seems to be similar to the whole structure.PSF models can estimate interface fractal dimension using soil pore size distribution data (PSD) and soil moisture retention curve (SWRC). The main objective of this study was to evaluate different fractal models to estimate the Ksparameter.
Materials and Methods: The Schaapetal data was used in this study. The complex consists of sixty soil samples. Soil texture, soil bulk density, soil saturated hydraulic conductivity and soil particle size distribution curve were measured by hydrometer method, undistributed soil sample, constant head method and wet sieve method, respectively for all soil samples.Soil water retention curve were determined by using pressure plates apparatus.The Ks parameter could be estimated by Ralws model as a function of fractal dimension by seven fractal models. Fractal models included Fuentes at al. (1996), Hunt and Gee (2002), Bird et al. (2000), Huang and Zhang (2005), Tyler and Wheatcraft (1990), Kutlu et al. (2008), Sepaskhah and Tafteh (2013).Therefore The Ks parameter can be estimated as a function of the DS (fractal dimension) by seven fractal models (Table 2).Sensitivity analysis of Rawls model was assessed by making changes)±10%, ±20% and±30%(in input parameters (porosity, fractal dimension and the intake air suction head).Some indices like RMSE, AIC and R2 were used to evaluate different fractal models.
Results and Discussion: The results of the sensitivity analysis of Rawls - Huang model, showed the least sensitivity to changes in porosity and suction entry air and the most sensitivity to changes in fractal dimension. The saturated hydraulic conductivity is underestimated by increasing the fractal dimension in Rawls - Huang model. The high sensitivity of the combined model to changes in fractal dimension, is considered as one of the model limitations.In other words, fractal dimension underestimation increased the error related to the hydraulic conductivity estimation. Sensitivity analysis of Ks regression model was done among parameters like bulk density, dry density, silt, sand, fractal dimension of particle size and porosity. Results showed less sensitivity to fractal dimension and porosity. The highest RMSE was 0.018 for fractal dimension and porosity (in the range of ±30% changes). The results showed that the amount of clay in the estimation of fractal dimension is of crucial importance. Statistical analyzes indicated the high accuracy of the PSF models based on soil texture data.Error indices showed the high accuracy of Rawls and three-phase fractal (pore- solid- fractal) models combination in estimating the Ks value. The results suggest that Huang and Zhang model, with the highest correlation, the least Root Mean Square Error and the least Akaike criteria among the studied fractal models for estimation of the Ks values. Fuentesand Hunt models, overestimated soil saturated hydraulic conductivity. Fuentes et al. (1996) as an experimental fractal model to estimate the saturated hydraulic conductivity indicatedvery poor results. Bird model had higher error values compared with the best model, (RMSE =0.73). This model fit well with the measured values compared to Sepaskhah and Taylor models particularly at low Ksvalues. Taylor's two-parameter model, which is similar to the Brooks - Corey and the Campbell model, was inserted in the fourth priority. The RMSE values of Sepaskhah and Taylor models were 0.62 (cm/h) and 0.55(cm/h) respectively. The fractal dimension is a function of soil texture. Heavy soils resulted in a larger fractal dimension and less hydraulic conductivity. Therefore, the Huang-Zhang model as a result of clay value using model (lower values for Ks), had a close fit with the measured data in probability distribution.
Conclusions: The results showed that the soil clay percent had a significant role in fractal dimension calculation.

کلیدواژه‌ها [English]

  • Fractal Dimension
  • Huang and Zhang fractal model
  • Rawls model
1- Ahmadi A., Neyshabouri M. R., and Asadi H. 2011. Relationship between Fractal Dimension of Particle Size Distribution and Some Physical Properties of Soils. Water and Soil Science Journal of Tabriz University, 20.1(4), 72-81. (In Farsi).
2- Bird N. R. A., Perrier E., and Rieu M. 2000. The water retention function for a model of soil structure with pore and solid fractal distributions. Europian Journal of soil science. 51, 55-63.
3- Brooks R. H., and Corey A. T. 1964. Hydraulic properties of porous media. Hydrology paper No. 3. Colorado State University, Fort Collins, CO.
4- Campbell C. S. 1985. Soil Physics with basic: Transport models for Soil-Plant Systems. Elsevier, Amsterdam.
5- Campbell G. S. 1974. A simple method for determining unsaturated hydraulic conductivity from moisture retention data. SoilScience. 117, 311-314.
6- Ersahin S., Gunal H., Kutlu T., Yetgin B., and Coban S. 2006. Estimating specific surface area and cation exchange capacity in soils using fractal dimension of particle-size distribution. Geoderma 136, 588–597.
7- Fallico C., Tarquis A. M., De Bartoloa S., and Veltria M. 2010. Scaling analysis of water retention curves forunsaturated sandy loam soils by using fractal geometry. Eur. J. Soil Sci. 61: 4 25_436.
8- Fuentes C., Vauclin M., Parlange J. Y., and Haverkamp R. 1996. A note on the soil-water conductivity of a fractal soil, Transport in Porous Media Journal. 23,31-36.
9- Ghahraman B., Omidi S., and Khoshnood Yazdi A. 2012. Scaling and fractal concepts in saturated hydraulic conductivity: comparison of some models, Iran Agricultural Research Journal, 31(1), 1-16.
10- Ghanbarian-Alavijeh B. 2014. Modeling physical and hydraulic properties of disordered porous media: Applications from percolation theory and fractal geometry. Ph. D. dissertation, Wright State University.
11- Ghanbarian-Alavijeh B., and Milla´n H. 2009. The relationshipbetween surface fractal dimension and soil water content atpermanent wilting point. Geoderma 151, 224_232.
12- Ghanbarian-Alavijeh B., Humberto M., and Huang G. 2011. A review of fractal, prefractal and pore-solid-fractal models for parameterizing the soil water retention curve, Canadian Journal of soil science. 91, 1-14.
13- Ghanbarian- Alavijeh B., Hunt A. G. 2012. Unsaturated hydraulic conductivity in porous media: Percolation theory, Geoderma 187–188, 77–84. doi:10.1016/j.geoderma. 2012.04.007
14- Gime´nez D., Perfect E., Rawls W. J., and Pachepsky Ya. 1997. Fractal models for predicting soil hydraulic properties: a review. Engergygeology. 48, 161-183.
15- Huang G., and Zhang R. 2005. Evaluation of soilwater retention curve with the pore-solid fractal approach.Geoderma 127, 52-61.
16- Huang G., Zhang R., and Huang Q. 2006. Modelling soil water retention curve with a fractal model, Pedosphere 16(2), 137-146.
17- Hunt A. G., and Gee G. W. 2002. Water-retention of fractalsoil models using continuum percolation theory: Tests ofHanford Site soils. VadoseZone Journal. 1: 252-260.
18- Hwang S. I., Lee K. P., Lee D. S., and Powers S. E. 2002. Models for estimating soil particle-size distributions. Soil Science Society of America Journal, 66, 1143–1150.
19- Khatamainejad S.A., Tabatabaei S.H., Mohammadi J., and Hoshmand A. 2011. Estimating soil saturated hydraulic conductivity Using fractal dimension theory in different soils, Iranian journal of irrigation and drainage, 5(1), p.1-8. (In Farsi).
20- Kravchenko A., and Zhang R. 1997. Estimating soil hydraulicconductivity from soil particle-size distribution. Proceedings ofthe International Workshop on Characterization and Measurement of the Hydraulic Properties of Unsaturated PorousMedia.
21- Kravchenko A., and Zhang R. 1998. Estimating the soil waterretention from particle-size distributions: a fractal approach.Soil science. 163: 171-179.
22- Kutlu T., Ersahin S., and Yetgin B. 2008. Relations between solid fractal dimention and some physical properties of soils formed over alluvial and colluvial deposits, Journal of food, Agriculture and Environmental, 6 (3&4): 445-449.
23- Miyazaki T. 1996. Bulk density dependence of air entry suctions and saturated hydraulic conductivities of soils. Soil Sci. 161: 484-490.
24- Milington R. J., and Quirk J. P. 1961. Permeability of porous solids. Trans. Faraday society. 57, 1200-1206.
25- Omidifard M., and Mousavi S. A.A. 2015. The hydraulic properties Estimation in calcareous soils of Badjgah, Fars province Using regression transfer functions , Journal of soil and water science, 29 (1),P.83-92.(In Farsi).
26- Perrier E., Bird N., and Rieu M. 1999. Generalizing a fractal model of soil structure: the pore-solid fractal approach. Geoderma, 88, 137_164.
27- Perrier EMA., and Bird NRA. 2003. The PSF model of soil structure: a multiscale approach. In: Pachepsky Y, Radcliffe DE, Selim HM, editors. Scaling methods in soil physics. New York: CRC Press. p. 1–18.
28- Perfect E., Rasiah V., and Kay B.D. 1992. Fractal dimensions of soil aggregate-size distributions calculated bynumber and mass. Soil science society American journal, 56, 1407-1409.
29- Rawls W. J., Brakensiek D. L., and Logsdon S. D. 1993. Predicting saturated hydraulic conductivity utilizing fractalprinciples. Soil science society of American journal. 57, 1193-1197.
30- Rawls W. J., Brakensiek D. L., and Saxton K. E. 1982. Estimation of soil water properties. Trans. ASAE 25:1316-1320 and 1328.
31- Schaap M.G., Shouse P.J., and Meyer P.D. 2003. Laboratory measurements of the unsaturated hydraulic properties at the vadose zone transport field study Site, Department of Energy under Contract DE-AC06-76RL01830.
32- Sepaskhah A.R., and Tafteh A. 2013. Pedotransfer function for estimation of soil-specific surface area using soilfractal dimension of improved particle-size distribution. Archives of Agronomy and Soil Science, 59(1), 93-103.
33- Shepard S. J. 1993. Using a fractal model to compute thehydraulic conductivity function. Soil science society of American journal, 57:300-306.
34- Tyler S. W., and Wheatcraft S. W. 1990. Fractal processes in soil water retention. Water Resources Research. 26, 1047-1054.
35- Wang K., Zhang R., and Wang F. 2005. Testing the pore-solidfractal model for the soil water retention function. Soil Science Society of America Journal, 69: 776_782.
36- Wagner B., Tarnawski V. R., Hennings V.M., Muller U., Wessolek G., and Plagge R. 2001. Evaluation of pedo-transfer functions for unsaturated soil hydraulic conductivity using an independent data set. Geoderma, 102, 275-297.
37- Yazdani V., Ghahreman B., Davari K., and Fazeli M.E. 2012. Using fractal dimension of particle size in estimating saturated hydraulic conductivity, Journal of Water and Soil, 26 (3), Jul-Aug, p. 648-659. (In Farsi).
38- Zhuang J., Yu G. R., Miyazaki T., and Nakayama K. 2000. Modeling effects of compaction on soil hydraulic properties―a NSMC scaling method for saturated hydraulic conductivity. Adv. Geoecol. 32: 144-153.
CAPTCHA Image